Computer Science

Data Pipelines with TensorFlow Data Services

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This AI course instructs students on the optimization of input pipelines, dataset segmentation, data preparation for training pipelines, and efficient ETL tasks using TensorFlow Data Services APIs.

Key AI Functions:

Tensorflow,Extraction, Transformation And Loading (ETL),Artificial Neural Network,TensorFlow Datasets,Data Pipelines

Description for Data Pipelines with TensorFlow Data Services

  • Utilize the Tensorflow Data Services APIs to execute ETL duties in an efficient manner.
  • Create train/validation/test divisions for any dataset, whether it is custom or available in the TensorFlow Hub Dataset library, by utilizing the divisions API.
  • Utilize a variety of modules and functions within the TFDS API to prepare your data for training pipelines.
  • Increase the efficacy of your workflow by identifying bottlenecks in your input pipelines and implementing input parallelization.
  • Level: Intermediate

    Certification Degree: Yes

    Languages the Course is Available: 21

    Offered by: On Coursera provided by DeepLearning.AI

    Duration: 11 hours (approximately)

    Schedule: Flexible

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